Implements the Goldilocks adaptive trial design for a time to event outcome using a piecewise exponential model and conjugate Gamma prior distributions. The method closely follows the article by Broglio and colleagues <doi:10.1080/10543406.2014.888569>, which allows users to explore the operating characteristics of different trial designs.
Version: 0.4.0 Depends: R (≥ 3.6.0), survival Imports: dplyr, parallel, pbmcapply, PWEALL, Rcpp, rlang, stats LinkingTo: BH, Rcpp Suggests: covr, testthat (≥ 3.0.0), knitr, rmarkdown Published: 2025-01-08 DOI: 10.32614/CRAN.package.goldilocks Author: Graeme L. Hickey [aut, cre], Ying Wan [aut], Thevaa Chandereng [aut] (bayesDP code as a template), Becton, Dickinson and Company [cph], Tim Kacprowski [ctb] (For code from fastlogrank R package.) Maintainer: Graeme L. Hickey <graemeleehickey at gmail.com> BugReports: https://github.com/graemeleehickey/goldilocks/issues License: GPL-3 URL: https://github.com/graemeleehickey/goldilocks NeedsCompilation: yes Language: en-US Materials: README NEWS CRAN checks: goldilocks results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=goldilocks to link to this page.
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